I want to solve automatically captchas like this one. I have been trying processing image to make Pytesseract be able to read it, but no success.
Can you help me?
image
I try this:
import cv2
from pytesseract import image_to_string
import pytesseract
img = cv2.imread("screenshot.png")
img = cv2.resize(img, (0, 0), fx=16, fy=16)
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
(h, w) = gry.shape[:2]
gry = cv2.resize(gry, (w*2, h*2))
cls = cv2.morphologyEx(gry, cv2.MORPH_CLOSE, None)
#thr = cv2.threshold(cls, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
thr = cv2.threshold(gry, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
txt = image_to_string(,lang='eng', config='--psm 11')
cv2.imwrite('prv.png', thr)
print(txt)
It would be really hard for AI/ML to solve a captcha. They are, at their core, designed to stop OCR.
Consider reading this:
https://www.cloudflare.com/learning/bots/how-captchas-work/
Related
https://imgur.com/a/zCmwUEf.jpg
this is the image from whom i am trying to extract text but unable to do so.
import contours
import cv2
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r'C:\Users\tan\tesseract\Tesseract-OCR\tesseract.exe'
# Opening the image & storing it in an image object
img = cv2.imread("C:/Users/tan/Desktop/my tppc bots/training challange - Copy/sample4.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh1 = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU | cv2.THRESH_BINARY_INV)
rect_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (18, 18))
dilation = cv2.dilate(thresh1, rect_kernel, iterations=1)
contours, hierarchy = cv2.findContours(dilation, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
im2 = img.copy()
file = open("recognized.txt", "w+")
file.write("")
file.close()
for cnt in contours:
x, y, w, h = cv2.boundingRect(cnt)
rect = cv2.rectangle(im2, (x, y), (x + w, y + h), (0, 255, 0), 2)
cropped = im2[y:y + h, x:x + w]
file = open("recognized.txt", "a")
text = pytesseract.image_to_string(cropped)
file.write(text)
file.write("\n")
this is my script
when i run it, it execute fine but when i open the text file it doesnt show any texts there just empty.
am i doing something wrong?
if someone can help me that be great
thanks!
I have found easyocr lib promising here.
Import the libs
import numpy as np
import easyocr
import cv2
read the image file
reader = easyocr.Reader(['en'],gpu = False) # load once only in memory.
image_file_name='capImage.png' # this is the screen snap of your image
image = cv2.imread(image_file_name)
get the text from image
image_text=(reader.readtext(image,detail=0)[0]) # output came as D F7BE1
print(image_text.replace(" ","")) # removed the space and output is : DF7BE1
clean up options for image :
image = cv2.imread(image_file_name)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
sharpen_kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
sharpen = cv2.filter2D(gray, -1, sharpen_kernel)
thresh = cv2.threshold(sharpen, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
height = 100
dim = (800, 800)
resized = cv2.resize(image, dim, interpolation = cv2.INTER_AREA)
now utilize the images.
image_text=(reader.readtext(thresh,detail=0)[0])
print(image_text.replace(" ",""))
image_text=(reader.readtext(sharpen,detail=0)[0])
print(image_text.replace(" ",""))
output:
I used below code for find cigarettes count in the below image using opencv python, but its not worked. Only this code finding some places only. i don't know what is the issue.. please help me
import numpy as np
import cv2
from PIL import Image
import sys
Path='D:\Artificial intelligence\Phyton'
filename='Test.png'
img = cv2.imread('D:\Artificial intelligence\Phyton\Test.png')
img1 = cv2.imread('D:\Artificial intelligence\Phyton\Test.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)
img[thresh == 255] = 0
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
erosion = cv2.erode(img, kernel, iterations = 1)
cv2.imwrite('D:\Artificial intelligence\Phyton\Test112.png',erosion)
def findcircles(img,contours):
minArea = 300;
minCircleRatio = 0.5;
for contour in contours:
(x,y),radius = cv2.minEnclosingCircle(contour)
center = (int(x),int(y))
radius = int(radius)
if radius > 5:
continue;
cv2.circle(img1, center, 1, (191, 255, 0), 2)
cv2.imwrite('D:\Artificial intelligence\Phyton\Test11234.png',img1)
img = cv2.imread("D:\Artificial intelligence\Phyton\Test112.png")
cv2.imwrite('D:\Artificial intelligence\Phyton\org.png',img)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret,threshold = cv2.threshold(gray, 199, 255,cv2.THRESH_BINARY_INV)
cv2.imwrite('D:\Artificial intelligence\Phyton\threshold.png',threshold)
blur = cv2.medianBlur(gray,7)
cv2.imwrite('D:\Artificial intelligence\Phyton\blur.png',blur)
laplacian=cv2.Laplacian(blur,-1,ksize = 5,delta = -50)
cv2.imwrite('D:\Artificial intelligence\Phyton\laplacian.png',laplacian)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(7,7))
dilation = cv2.dilate(laplacian,kernel,iterations = 1)
cv2.imwrite('D:\Artificial intelligence\Phyton\dilation.png',dilation)
result= cv2.subtract(threshold,dilation)
cv2.imwrite('D:\Artificial intelligence\Phyton\result.png',result)
contours, hierarchy = cv2.findContours(result,cv2.RETR_LIST,cv2.CHAIN_APPROX_NONE)
findcircles(gray,contours)
Image :
enter image description here
My result:
enter image description here
I am trying to get the number below a barcode in an image. I have tried the same code with some other images and works fine but not for that image
Here's the image
And here is the code till now
def readNumber():
image = cv2.imread(sTemp)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (3,3), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=1)
invert = 255 - opening
data = pytesseract.image_to_string(invert, lang='eng', config='--psm 6 -c tessedit_char_whitelist=0123456789')
print(data)
try:
data = re.findall('(\d{9})\D', data)[0]
except:
data = ''
return data
And I used it using this line
readNumber()
Here's another example
This is the last example I promise
I tried this with the third example and it works
img = cv2.imread("thisimage.png")
blur = cv2.GaussianBlur(img, (3,3), 0)
#gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
txt = pytesseract.image_to_string(blur)
print(txt)
But how I adopt all the cases to work with the three cases?
I tried such a code but couldn't implement the thrid case
import pytesseract, cv2, re
def readNumber(img):
img = cv2.imread(img)
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
try:
txt = pytesseract.image_to_string(gry)
#txt = re.findall('(\d{9})\D', txt)[0]
except:
thr = cv2.adaptiveThreshold(gry, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 51, 4)
txt = pytesseract.image_to_string(thr, config="digits")
#txt = re.findall('(\d{9})\D', txt)[0]
return txt
# M5Pr5 191876320
# RWgrP 202131290
# 6pVH4 193832560
print(readNumber('M5Pr5.png'))
You don't need any preprocessing methods or configuration for the input image. Since there is no artifacts in the image.
import cv2
import pytesseract
img = cv2.imread("RWgrP.png")
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
txt = pytesseract.image_to_string(gry)
print(txt)
Result:
202131290
My pytesseract version is 4.1.1
Update-1
The second image requires preprocessing
If you apply adaptive-thresholding:
But the output also consists of unwanted characters. Therefore if you set the configuration to digits, the result will be:
193832560
Update-2
For the third image, you need to change the adaptive method, using ADAPTIVE_THRESH_MEAN_C will result in:
191876320
The rest are same.
Code:
import cv2
import pytesseract
img = cv2.imread("6pVH4.png")
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thr = cv2.adaptiveThreshold(gry, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 51, 4)
txt = pytesseract.image_to_string(thr, config="digits")
print(txt)
cv2.imshow("thr", thr)
cv2.waitKey(0)
def resolve(img_path):
image = Image.open(img_path)
new_image = Image.new("RGBA", image.size, "WHITE") # Create a white rgba background
new_image.paste(image, (0, 0), image) # Paste the image on the background.
new_image.convert('RGB').save(img_path, "JPEG") # Save as JPEG
enhancedImage = enhance(img_path)
return pytesseract.image_to_string(img_path)
def enhance(img_path):
image1 = cv2.imread(img_path)
#print(image1)
img = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
ret, thresh1 = cv2.threshold(img, 180, 255, cv2.THRESH_BINARY_INV)
#thresh = 50
#im_bw = cv2.threshold(thresh3, thresh, 255, cv2.THRESH_BINARY)[1]
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (1, 2))
erosion = cv2.erode(thresh1, kernel, iterations = 1)
return erosion
I'm trying to solve captcha for above images. Tried converting transparent bg to white and then enchancing the image but results are not correct.
Let me start with the potential problem with your code
def enhance(img_path):
image1 = cv2.imread(img_path)
Now, if you read it with imread the result will be:
You can't read it with pytesseract from the output image.
This is a known issue stated in this answer: cv2 imread transparency gone
As mentioned in the answer:
put a white image behind the transparent one an with that you solve the problem.
We will apply the same technique and now result will be:
As for the second image result will be:
We will be doing the following steps for efficiently reading from the output image:
Resize the image
Apply adaptive-threshold
For the first image the result will be:
For the second image the result will be:
Now when you read it with pytesseract with mode 6 (modes), result will be:
3daab
b42yb
Code:
import cv2
from PIL import Image
from pytesseract import image_to_string
def save_transparent_image(image_path, save_name):
image = Image.open(image_path).convert("RGBA")
canvas = Image.new(mode='RGBA',
size=image.size, color=(255, 255, 255, 255))
canvas.paste(image, mask=image)
canvas.save(save_name, format="PNG")
img_lst = ["o3upS.png", "kGpYk.png"]
for i, img_name in enumerate(img_lst):
save_image = "captcha" + str(i) + ".png"
save_transparent_image(img_name, save_image)
# Step 1: Resize the image
img = cv2.imread(save_image)
(h, w) = img.shape[:2]
img = cv2.resize(img, (w*2, h*2))
# Step 2: Apply adaptive-threshold
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thr = cv2.adaptiveThreshold(gry, 255, cv2.ADAPTIVE_THRESH_MEAN_C,
cv2.THRESH_BINARY, 33, 79)
# Step 3: Read the threshold image
txt = image_to_string(thr, config="--psm 6")
txt = txt.split("\n")[0]
print(txt)
Question Will this code will works for the other captchas?
No, it won't. Unless the captchas are similar to the given example. You need to change the adaptive-threshold's block-size and C parameters, see if it works.
i am using tesseract 4.0.0-beta.1
I have the following image
ocr image
i have converted this image using opencv
converted image
img = cv2.imread(image, cv2.IMREAD_GRAYSCALE)
img = cv2.resize(img, None, fx=5, fy=5, interpolation=cv2.INTER_LINEAR)
img = cv2.medianBlur(img, 9)
_, img = cv2.threshold(img, 185, 255, cv2.THRESH_BINARY)
my tesseract commend
tesseract image.png stdout -l eng-best --oem 1 --psm 7
getting result: NVRG nk
but result should be : nvRGnk
Starting from your converted image, just need a little more filtering
nvRGnk
import cv2
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"
image = cv2.imread('2.png',0)
image = 255 - image
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
close = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel, iterations=2)
dilate_kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2,2))
dilate = cv2.dilate(close, dilate_kernel, iterations=1)
result = 255 - dilate
data = pytesseract.image_to_string(result, lang='eng',config='--psm 13')
print(data)
cv2.imshow('result', result)
cv2.waitKey()